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83
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CORR
2010
Springer
219views Education» more  CORR 2010»
14 years 9 months ago
Clustering high dimensional data using subspace and projected clustering algorithms
: Problem statement: Clustering has a number of techniques that have been developed in statistics, pattern recognition, data mining, and other fields. Subspace clustering enumerate...
Rahmat Widia Sembiring, Jasni Mohamad Zain, Abdull...
ALENEX
2001
215views Algorithms» more  ALENEX 2001»
14 years 11 months ago
An Empirical Study of a New Approach to Nearest Neighbor Searching
In nearest neighbor searching we are given a set of n data points in real d-dimensional space, d , and the problem is to preprocess these points into a data structure, so that give...
Songrit Maneewongvatana, David M. Mount
73
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SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
14 years 11 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà
PKDD
2000
Springer
144views Data Mining» more  PKDD 2000»
15 years 1 months ago
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
: One way to scale up clustering algorithms is to squash the data by some intelligent compression technique and cluster only the compressed data records. Such compressed data recor...
Markus M. Breunig, Hans-Peter Kriegel, Jörg S...
CIKM
2004
Springer
15 years 3 months ago
Scalable sequential pattern mining for biological sequences
Biosequences typically have a small alphabet, a long length, and patterns containing gaps (i.e., “don’t care”) of arbitrary size. Mining frequent patterns in such sequences ...
Ke Wang, Yabo Xu, Jeffrey Xu Yu